Key features
- Distributed tracing — end-to-end request trace collection across APAC microservice boundaries
- Adaptive sampling — dynamic trace sampling that captures high-value traces without full-volume storage
- Service dependency graph — automatic visualisation of inter-service call relationships from trace data
- OTLP support — native OpenTelemetry Protocol ingestion for OTel-instrumented APAC applications
- Multi-backend storage — Elasticsearch, OpenSearch, Cassandra, and Badger trace storage options
- Trace comparison — side-by-side trace comparison for APAC performance regression analysis
- Kubernetes native — Jaeger Operator for Kubernetes-native deployment and lifecycle management
Best for
- APAC microservices engineering teams wanting open-source distributed tracing without commercial observability licensing
- Platform and SRE teams diagnosing latency and cascading failures across APAC Kubernetes service architectures
- Teams standardising on OpenTelemetry instrumentation wanting a CNCF-standard trace backend
- APAC organisations with data sovereignty requirements preferring self-hosted trace storage over commercial SaaS
Limitations to know
- ! Jaeger requires self-hosted backend storage (Elasticsearch or Cassandra) — APAC teams must manage trace storage operational overhead
- ! Jaeger UI is functional but less polished than commercial alternatives — consider Grafana Tempo + Grafana for richer APAC trace exploration
- ! No built-in metrics or log correlation in Jaeger alone — full APAC observability requires Prometheus + Loki or Grafana stack alongside Jaeger
- ! Scaling Jaeger collector and storage for high-volume APAC production traffic requires capacity planning expertise
About Jaeger
Jaeger is a CNCF (Cloud Native Computing Foundation) graduated open-source distributed tracing platform that provides APAC microservices and Kubernetes engineering teams with end-to-end request trace collection, adaptive sampling, trace visualisation, and service dependency mapping — enabling APAC platform and SRE teams to understand latency, identify performance bottlenecks, and diagnose failures across distributed APAC service architectures.
Jaeger's core value for APAC microservices teams is making distributed request flows visible. In a monolith application, a slow database query that causes user-facing latency is straightforward to identify — the application's profiling tools show the slow function. In a microservices architecture where a user request traverses 8 services before returning a response, the same slow database query in service 6 is invisible to surface-level latency monitoring (which sees only the end-to-end response time) and requires distributed tracing to identify which service in the call chain is the bottleneck.
Jaeger's trace collection model — where application services emit trace spans to a Jaeger collector, spans are assembled into complete traces representing end-to-end request flows, and complete traces are stored in a backend (Elasticsearch, OpenSearch, Cassandra, or Badger for development) — captures the full distributed request context that enables APAC SRE teams to diagnose latency incidents, trace request flows through APAC service architectures, and identify cascading failure patterns across service boundaries.
Jaeger's adaptive sampling — which dynamically adjusts the trace sampling rate based on traffic volume and trace quality signals, ensuring that high-value traces (error traces, slow traces) are always captured while normal-path traces at high volume are sampled — enables APAC engineering teams to instrument production traffic without the storage and processing overhead of capturing 100% of all traces at high traffic volumes.
Jaeger's integration with OpenTelemetry — Jaeger accepts OTLP (OpenTelemetry Protocol) trace data natively in Jaeger 1.35+, enabling APAC teams that instrument applications with OpenTelemetry SDKs to export traces to Jaeger without additional agent configuration — aligns with the APAC industry direction of OpenTelemetry as the standard instrumentation layer and Jaeger as one of multiple compatible trace backends.
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